Evaluation Methodology for Image Testbed and Content-Based Retrieval

Suny At Buffalo, Amherst NY

Investigators

Abstract

The project aims at developing an evaluation methodology for content-based image retrieval. The research involves: (1) Measurement of the complexity of image testbeds which can be used to quantitatively determine the degree of difficulty in retrieving images from the image testbeds, and (2) Comparison of the performance of different retrieval approaches which can quantitatively give an objective ranking of the performance of the retrieval approaches. The project designs a general framework of image feature representations which can be used as a vehicle to conduct statistical analysis on images and forms a basis for establishing the evaluation methodology. Using this framework, the evaluation method can measure the complexity of the image databases by their cross entropy and rank the retrieval approaches by their cross entropy with respect to a particular testbed. The image testbeds can thus be compared with each other on their complexity in supporting image querying. Furthermore, the retrieval techniques can be compared with each other without using queries so the human subjectivity is avoided. The algorithms developed in this project will be a valuable asset for the community to eventually establish a general theory of the evaluation methodology for content-based image retrieval research.